WRANGLERS
Photo by Matt Collamer on Unsplash
Generosity is the most natural outward expression of an inner attitude of compassion and loving-kindness…
— The Dalai Lama XIV
We have a natural instinct to help others. Wealth doesn’t come into it. Citizens of relatively poor countries such as Myanmar and Indonesia are some of the most generous. They help strangers. They donate money. They volunteer time. The top 20 includes countries that have suffered massive instability. Haiti. Liberia. Sierra Leone. Shared human values, shining through.
Let’s take a closer look at the situation.
df = read.csv("archetypes/worlds-most-generous/worlds-most-generous.csv", header = TRUE, stringsAsFactors = FALSE)
df# Select only the needed
df_complete <- select(df, c("Country", "Overall_CAF_Giving_Index_Score_Percent", "GDP_per_capita_current_USD", "population"))
# Make sure all visual variables are proper data types
df_complete$Overall_CAF_Giving_Index_Score_Percent <- parse_number(df_complete$Overall_CAF_Giving_Index_Score_Percent)
df_complete$GDP_per_capita_current_USD <- parse_number(df_complete$GDP_per_capita_current_USD)
df_complete$population <- parse_number(df_complete$population)
# Make sure we don't factor empty strings
df_complete <- filter(df_complete, nchar(Country) > 0)
# Factor the string fields
df_complete$Country <- as.factor(df_complete$Country)
# Remove incomplete cases
df_complete <- df_complete[complete.cases(df_complete), ]
df_complete# measures to use for quadrant placement
gdp_average <- mean(df_complete$GDP_per_capita_current_USD)
gdp_min <- min(df_complete$GDP_per_capita_current_USD)
gdp_max <- max(df_complete$GDP_per_capita_current_USD)
generosity_average <- mean(df_complete$Overall_CAF_Giving_Index_Score_Percent)
generosity_min <- min(df_complete$Overall_CAF_Giving_Index_Score_Percent)
generosity_max <- max(df_complete$Overall_CAF_Giving_Index_Score_Percent)
# Create a color variable for a manual scale
df_complete <- df_complete %>% mutate(color = ifelse( GDP_per_capita_current_USD < gdp_average & Overall_CAF_Giving_Index_Score_Percent > generosity_average, 'R', 'B'))
df_complete# theme parameters
theme_opts <- theme(
text = element_text(family = "inconsolata"),
legend.position = "none",
legend.title = element_blank(),
axis.text = element_blank(),
axis.line = element_blank(),
axis.ticks = element_blank(),
#axis.title = element_blank(),
panel.grid = element_blank(),
# panel.grid.major = element_line(linetype = "dotted"),
# panel.grid.minor = element_blank(),
panel.background = element_rect(fill="#B3E5FC", colour="#B3E5FC"),
panel.border = element_blank(),
plot.background = element_rect(fill="#B3E5FC", colour="white"),
plot.title = element_text(vjust = 3.0),
plot.subtitle = element_text(vjust = 3.0),
plot.margin = unit(c(0.5,0.5,0.5,0.5), "in")
)
color_palette <- c("B" = "#111111", "R" = "#f15a24")
v1 <- ggplot(df_complete) +
geom_point_interactive(aes(x = GDP_per_capita_current_USD,
y = Overall_CAF_Giving_Index_Score_Percent,
size = population,
color = color,
tooltip = paste0("Country: ", Country, "\n",
"Overall_CAF_Giving_Index_Score_Percent: ", Overall_CAF_Giving_Index_Score_Percent, "%\n",
"GDP_per_capita_current_USD: ", GDP_per_capita_current_USD, "\n",
"population: ", population),
data_id = row.names(df_complete)),
shape = 21, fill = "#E1F5FE", alpha = 1.0 ) + # or fill = "NA"
geom_text_repel(data=filter(df_complete, population>mean(population)),
aes(x = GDP_per_capita_current_USD, y = Overall_CAF_Giving_Index_Score_Percent, label = Country, color = color),
family = 'inconsolata', size = 4, force = 0.5, nudge_x = 0.25, segment.size = 0.2, segment.color = "grey50", direction = "both", hjust = 0) +
scale_x_continuous(trans = "log2") +
scale_y_continuous() +
scale_size("population", range = c(2, 40)) +
scale_color_manual(guide = FALSE, values = color_palette) +
coord_cartesian(clip = 'off') +
labs(x="GDP",
y="Generosity",
title = "Some of the World's Poorest Nations\nare also the Most Generous",
caption = "source: Charities Aid Foundation, Information is Beautiful") +
theme_minimal(base_family = "inconsolata", base_size = 16) +
theme_opts
girafe(ggobj = v1, width_svg = 1280/72, height_svg = 720/72,
options = list(
opts_sizing(rescale = TRUE, width = 1.0),
opts_hover(css = "fill:#81D4FA;")
)
)v2 <- v1 + geom_hline(yintercept = generosity_average, linetype = "dashed", color = "#f15a24") +
geom_vline(xintercept = gdp_average, linetype = "dashed", color = "#f15a24") +
annotate("text", x = gdp_min, y = generosity_max,
label = "poor & generous countries",
hjust = 0.3, vjust = 0.5, size = 5, color = "#f15a24", family = "inconsolata", fontface = 2) +
annotate("text", x = gdp_max, y = generosity_max,
label = "rich & generous",
hjust = 0.55, vjust = 0.5, size = 5, color = "#111111", family = "inconsolata", fontface = 2) +
annotate("text", x = gdp_min, y = generosity_min,
label = "poor & less generous",
hjust = 0.3, vjust = 0, size = 5, color = "#111111", family = "inconsolata", fontface = 2) +
annotate("text", x = gdp_max, y = generosity_min,
label = "rich & less generous",
hjust = 0.7, vjust = 0, size = 5, color = "#111111", family = "inconsolata", fontface = 2) +
annotate("text", x = gdp_average, y = generosity_max,
label = "HIGH GENEROSITY",
hjust = 0.5, vjust = -4.0, size = 5, color = "#f15a24", family = "inconsolata", fontface = 1) +
annotate("text", x = gdp_average, y = generosity_min,
label = "LOW GENEROSITY",
hjust = 0.5, vjust = 5.0, size = 5, color = "#f15a24", family = "inconsolata", fontface = 1) +
annotate("text", x = gdp_min, y = generosity_average,
label = "LOW WEALTH",
hjust = 0.8, vjust = 1.5, size = 5, color = "#f15a24", family = "inconsolata", fontface = 1) +
annotate("text", x = gdp_max, y = generosity_average,
label = "HIGH WEALTH",
hjust = 0.3, vjust = 1.5, size = 5, color = "#f15a24", family = "inconsolata", fontface = 1)
girafe(ggobj = v2, width_svg = 1280/72, height_svg = 720/72,
options = list(
opts_sizing(rescale = TRUE, width = 1.0),
opts_hover(css = "fill:#81D4FA;")
)
)